Triple

T516712
Position Surface form Disambiguated ID Type / Status
Subject Academy Award for Best Actor E10723 entity
Predicate eligibilityScope P1130 FINISHED
Object primarily English-language and U.S.-released films LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: primarily English-language and U.S.-released films | Statement: [Academy Award for Best Actor, eligibilityScope, primarily English-language and U.S.-released films]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: eligibilityScope
Context triple: [Academy Award for Best Actor, eligibilityScope, primarily English-language and U.S.-released films]
  • A. eligibilityLevel
    Indicates the degree or tier of qualification an entity has for a given benefit, service, or status.
  • B. eligibility
    Indicates that an entity meets the required conditions or qualifications to participate in, receive, or perform something.
  • C. eligibilityCriteria chosen
    Indicates the conditions or requirements that must be satisfied for an entity to qualify for or be considered eligible for something.
  • D. eligibilitySameAs
    Indicates that two entities share the same eligibility status or criteria for a given program, benefit, or condition.
  • E. eligibleBorrower
    Indicates that an entity meets the required conditions to be allowed to borrow (e.g., money, items, or resources) under a given set of rules or policies.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f184c3a481909bf60bb627b0ea88 completed Feb. 28, 2026, 1:45 p.m.
PD Predicate disambiguation batch_69a2f0151e8c81909a82b58ac0515eba completed Feb. 28, 2026, 1:39 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.